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THz wave regulates molecular conformational transition

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THz wave regulates molecular conformational transition

IEEE International Conference on Plasma Science (ICOPS)

作者： S. Gu Z. Zhu Y. Li School of Optical-Electrical Computer Engineering University of Shanghai for Science and Technology Shanghai China Innovation Laboratory of Terahertz Biophysics National Innovation Institute of Defense Technology Beijing China

ISBN: (数字)9798350360912

ISBN: (纸本)9798350360929

Conversion of molecular conformations is closely related to many important biological processes. It follows that modulating the conformation of a molecular is a promising way to regulate its biological behavior. Recently terahertz (THz) waves have been proven as effective stimuli in altering the molecular dynamics as the transitions between vibrational or rotational energy levels of molecules follow the absorption of electromagnetic radiations in the far- or mid-infrared band (taken as the generalized THz band for convenience). There have been extensive efforts devoted into studying the rich bioeffects of THz waves and the underlying mechanisms [1–5]. Nevertheless, the electromagnetic frequencies are mostly in the relatively high-frequency THz band (approximately >30 THz). How the low-frequency THz waves affect the molecules remains elusive. In this work, we demonstrate through molecular dynamics simulations that specific low-frequency THz radiations can well switch the retinal in the rhodopsin among its dominant conformation and other secondary ones. The interconversion of the retinal conformations is uncovered due to resonance of the external THz fields with the retinal molecules. More specifically, the resonance absorption leads to an increase of the kinetic energy, promotes the chance of the retinal overcoming its free energy barriers, and ultimately makes the conformational transitions. In addition, it is noteworthy that for this work we propose to use the angular momenta based spectral analysis method to interpret the molecular rotations and successfully pinpoint the effective THz frequencies. The findings of this study expand the scope of THz technologies in manipulating molecular conformations, which could be widely applied in a variety of biological processes.

关键词： Absorption Biological processes Switches Retina Resonance Energy states Plasmas

Enhancing the Performance of Machine Learning Classification Models

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Enhancing the Performance of Machine Learning Classification...

International Symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Cihat Talat Akpinar Özcan Koşar Akif Durdu Computer Engineering Research and Development Elfatek Elektronik Ltd. Co. Konya Turkey Department of Electrical and Electronics Engineering Robotics Automation Control Laboratory (RAC-LAB) Konya Technical University Konya Turkey

ISBN: (数字)9798331515799

ISBN: (纸本)9798331515805

This study aims to compare and improve the performance of four different machine learning algorithms (Naive Bayes, Multi-Layer Perceptron (MLP), Decision Trees, and Support Vector Machines (SVM)) in classification problems. The analyses emphasize the impact of data preprocessing steps and hyperparameter optimization on model performance. As part of the data preprocessing, missing values were imputed, categorical data were transformed into numerical data, and normalization procedures were applied. It was observed that normalization significantly enhanced the performance of the MLP and SVM algorithms in particular. Furthermore, additional improvements in accuracy rates were achieved through hyperparameter optimization. Naive Bayes and Decision Trees were found to exhibit stable performance regardless of data scaling. This study demonstrates that proper data preprocessing and model selection can significantly enhance algorithm performance in classification problems.

关键词： Support vector machines Accuracy Machine learning algorithms Data preprocessing Hyperparameter optimization Data models Bayes methods Classification algorithms Numerical models Decision trees

YOLO: An Efficient Terahertz Band Integrated Sensing and Communications Scheme with Beam Squint

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arXiv 2023年

作者： Luo, Hongliang Gao, Feifei Lin, Hai Ma, Shaodan Vincent Poor, H. Department of Automation Tsinghua University Beijing China Department of Electrical and Electronic Systems Engineering Graduate School of Engineering Osaka Metropolitan University Osaka Sakai Japan State Key Laboratory of Internet of Things for Smart City The Department of Electrical and Computer Engineering University of Macau China Department of Electrical and Computer Engineering Princeton University PrincetonNJ United States

Using communications signals for dynamic target sensing is an important component of integrated sensing and communications (ISAC). In this paper, we propose to utilize the beam squint effect to realize fast non-cooperative dynamic target sensing in massive multiple input and multiple output (MIMO) Terahertz band communications systems. Specifically, we construct a wideband channel model of the echo signals, and design a beamforming strategy that controls the range of beam squint by adjusting the values of phase shifters and true time delay lines. With this design, beams at different subcarriers can be aligned along different directions in a planned way. Then the received echo signals at different subcarriers will carry target information in different directions, based on which the targets’ angles can be estimated through sophisticatedly designed algorithm. Moreover, we propose a supporting method based on extended array signal estimation, which utilizes the phase changes of different frequency subcarriers within different orthogonal frequency division multiplexing (OFDM) symbols to estimate the distances and velocities of dynamic targets. Interestingly, the proposed sensing scheme only needs to transmit and receive the signals once, which can be termed as You Only Listen Once (YOLO). Compared with the traditional ISAC methods that require time consuming beam sweeping, the proposed one greatly reduces the sensing overhead. Simulation results are provided to demonstrate the effectiveness of the proposed schemes. Copyright © 2023, The Authors. All rights reserved.

关键词： Orthogonal frequency division multiplexing

Cross-Domain Knowledge Transfer for Underwater Acoustic Classification Using Pre-trained Models

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arXiv 2024年

作者： Mohammadi, Amirmohammad Kelhe, Tejashri Carreiro, Davelle Van Dine, Alexandra Peeples, Joshua Department of Electrical and Computer Engineering Texas A&M University College StationTX United States Massachusetts Institute of Technology Lincoln Laboratory LexingtonMA United States

Transfer learning is commonly employed to leverage large, pre-trained models and perform fine-tuning for downstream tasks. The most prevalent pre-trained models are initially trained using ImageNet. However, their ability to generalize can vary across different data modalities. This study compares pretrained Audio Neural Networks (PANNs) and ImageNet pretrained models within the context of underwater acoustic target recognition (UATR). It was observed that the ImageNet pretrained models slightly out-perform pre-trained audio models in passive sonar classification. We also analyzed the impact of audio sampling rates for model pre-training and fine-tuning. This study contributes to transfer learning applications of UATR, illustrating the potential of pre-trained models to address limitations caused by scarce, labeled data in the UATR domain. © 2024, CC BY.

关键词： Underwater acoustics

Sample-Based Conservative Bias Linear Power Flow Approximations

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arXiv 2024年

作者： Buason, Paprapee Misra, Sidhant Molzahn, Daniel K. Los Alamos National Laboratory Los AlamosNM87545 United States School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30313 United States

The power flow equations are central to many problems in power system planning, analysis, and control. However, their inherent non-linearity and non-convexity present substantial challenges during problem-solving processes, especially for optimization problems. Accordingly, linear approximations are commonly employed to streamline computations, although this can often entail compromises in accuracy and feasibility. This paper proposes an approach termed Conservative Bias Linear Approximations (CBLA) for addressing these limitations. By minimizing approximation errors across a specified operating range while incorporating conservativeness (over- or under-estimating quantities of interest), CBLA strikes a balance between accuracy and tractability by maintaining linear constraints. By allowing users to design loss functions tailored to the specific approximated function, the bias approximation approach significantly enhances approximation accuracy. We illustrate the effectiveness of our proposed approach through several test cases. © 2024, CC BY-NC-ND.

关键词： Electric load flow

Near-Optimal Near-Field Beam Training: From Searching to Inference

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IEEE Transactions on Wireless Communications 2025年

作者： Xu, Zhuo Zhang, Zijian Dai, Linglong Tsinghua University Department of Electronic Engineering Beijing100084 China Tsinghua University State Key Laboratory of Space Network and Communications Beijing100084 China Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science CambridgeMA02139 United States

In extremely large-scale multiple input multiple output (XL-MIMO) systems, near-field beam training (NFBT) is an essential way to acquire channel state information (CSI) knowledge. To reduce the high training overhead caused by the distance dimension of the near-field codebook, some overhead-reduced NFBT schemes were proposed in the literature. However, existing schemes ignore the correlation between different near-field beams, which promises to provide prior knowledge for the reduction of training overhead. Aligned with this vision, this paper proposes a Bayesian regression (BAR)-based NFBT scheme, which fully utilizes the strong correlation between near-field codewords to achieve near-optimal and low-overhead NFBT. Specifically, inspired by Bayesian regression, we model the received signal corresponding to different codewords as a Gaussian process. Then, the optimal codeword can be determined by iteratively updating the posterior distribution and designing the codeword searching order. Besides, different codeword inference strategies are analyzed and compared. The proposed scheme only requires searching for a few codewords instead of the entire codebook thus avoiding the high training overhead. Simulation results verify that, compared to the existing schemes, the proposed scheme can significantly reduce the training overhead while maintaining a near-optimal achievable rate performance. © 2002-2012 IEEE.

关键词： Codes (symbols)

Data-driven local operator finding for reduced-order modelling of plasma systems: II. Application to parametric dynamics

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arXiv 2024年

作者： Faraji, Farbod Reza, Maryam Knoll, Aaron Kutz, J. Nathan Plasma Propulsion Laboratory Department of Aeronautics Imperial College London London United Kingdom Department of Applied Mathematics and Electrical and Computer Engineering University of Washington Seattle United States

The dynamics of many real-world systems is dependent on certain parameters. These are either intrinsic to the system, inherently evolving over time, or that are external and enable controlling the system’s behavior. A fully generalizable model shall be able to reliably represent these parametric behaviors. Plasma technologies serve as an example of parametric dynamical systems. For instance, in a Hall thruster – an industrially important plasma propulsion technology for spacecrafts – the dominant plasma phenomena governing the device’s global dynamics change as the "self-sustained electric field" parameter varies over one characteristic cycle of the system. In addition, changing the control parameters, such as the intensity of externally applied magnetic field or the applied discharge voltage can majorly alter the dynamics of the thruster. In this Part II, we demonstrate that our novel data-driven local operator finding algorithm, Phi Method, which was discussed in Part I, can effectively learn the parametric dynamics so as to faithfully predict the systems’ behavior over unseen parameter spaces. We describe two adaptations of Phi Method toward parametric dynamics discovery, namely, the "parametric Phi Method" and the "ensemble Phi Method". Two demonstration cases are adopted: one, the 2D problem of a fluid flow past a cylinder, and the other, the 1D problem of Hall thruster plasma discharge. For the first test case, the "parametric Phi Method" is assessed comparatively against the parametric implementation of OPT-DMD. The predictive performance of the parametric Phi Method notably surpassed that of the "parametric OPT-DMD" in the fluid test case. Across both test cases, the parametric and ensemble Phi Method were rather equivalently well able to recover the governing parametric PDEs and provide accurate predictions over the test parameters. Analysis of the ensemble ROMs underlined that Phi Method learns the coefficients of the dominant terms in the dynamics with ve

关键词： Dynamic mode decomposition

Utility-Scale Shared Energy Storage Deployment: Challenges, Research Gaps, and Opportunities

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Utility-Scale Shared Energy Storage Deployment: Challenges, ...

Resilience Week (RWS)

作者： Mukesh Gautam Di Wu Mohammed Ben-Idris Electricity Infrastructure & Buildings Division Pacific Northwest National Laboratory Richland Washington USA Department of Electrical and Computer Engineering Michigan State University East Lansing Michigan USA

ISBN: (数字)9798350388985

ISBN: (纸本)9798350388992

Although community energy storage (CES) and behind-the-meter (BTM) energy storage systems have been widely used to offer homeowners and communities a variety of localized benefits, their scalability and grid support functionalities are limited. On the other hand, utility-scale shared energy storage (USES) systems may offer a number of benefits for grid integration, scalability, and economic viability. When compared to BTM and CES alternatives, these large-scale systems provide more storage capacity, more efficient operations, and more economically viable options. The deployment of USES presents opportunities for optimizing grid performance, integrating renewable energy resources, and improving energy security at the community level. However, significant research gaps exist in optimizing the integration and operation of these systems, especially to allocate energy for consumer use, grid services, and enhancing energy resilience. This paper reviews the literature in this regard, focusing on the opportunities, research gaps, and challenges associated with USES deployment. Firstly, the paper provides an overview of USES systems and emphasizes their benefits. Secondly, the key challenges are identified, and research gaps associated with the operation and integration of these systems are highlighted. Lastly, some potential solutions and opportunities that can be adopted to facilitate the rapid deployment and management of USES are presented. Technological, economic, regulatory, and environmental aspects are also discussed in this paper, providing an overview of the current state and future prospects of this technology.

关键词： Economics Renewable energy sources Technological innovation Reviews Scalability Security Stakeholders Resource management Energy storage Resilience

Radar Clutter Covariance Estimation: A Nonlinear Spectral Shrinkage Approach 48

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Radar Clutter Covariance Estimation: A Nonlinear Spectral Sh...

48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Jain, Shashwat Krishnamurthy, Vikram Rangaswamy, Muralidhar Kang, Bosung Gogineni, Sandeep Cornell University Electrical and Computer Engineering NY United States Wright Patterson Airforce Base Air Force Research Laboratory OH United States University of Dayton Research Institute DaytonOH United States Information Systems Laboratories Inc. DaytonOH United States

ISBN: (纸本)9781728163277

In this paper, we exploit the spiked covariance structure of the clutter plus noise covariance matrix for adaptive radar signal processing. Using state-of-the-art techniques from mathematical finance and high dimensional statistics we propose a non-linear shrinkage-based rotation invariant spiked covariance matrix estimator. We compare the proposed estimator with Rank Constrained Maximum Likelihood (RCML)-Expected Likelihood (EL) covariance estimator using the Challenge dataset generated from RFView. We demonstrate that the computation-time for the proposed estimator is less than the RCML-EL estimator with identical Signal to Clutter plus Noise (SCNR) performance for the Challenge dataset. We derive the lower bound and upper bound for the normalized SCNR and empirically show that RCML-EL and the proposed estimator perform within these derived bounds for the Challenge dataset. We state the convergence for the spiked eigenvalues of the estimator. © 2023 IEEE.

关键词： Shrinkage